This model utilizes a custom MLP architecture optimized for GGUF deployment. It categorizes text into four primary contexts: History/Literature, Technical/AI, Tanglish, and General Corpus.

Developed for the open-source community by Crossberryweb.

Crossberry/tamila

Live Demo (HF Space): <a href="https://huggingface.co/spaces/Crossberry/tamila-test-app" target="_blank" rel="noopener noreferrer" class="text-blue-400 hover:text-blue-300 underline underline-offset-2 transition-colors">https://huggingface.co/spaces/Crossberry/tamila-test-app
Web Deployment: <a href="https://crossberry.vercel.app" target="_blank" rel="noopener noreferrer" class="text-blue-400 hover:text-blue-300 underline underline-offset-2 transition-colors">crossberry.vercel.app
Dataset Repository: <a href="https://huggingface.co/datasets/crossberryweb/tamila" target="_blank" rel="noopener noreferrer" class="text-blue-400 hover:text-blue-300 underline underline-offset-2 transition-colors">Hugging Face Tamila

🚀 Tamila Master v0.3

🔗 Project Links

📊 Model Benchmarks

🛠 Future Roadmap

📖 More Info

Crossberry/
tamila